31 lines
1.9 KiB
Markdown
31 lines
1.9 KiB
Markdown
# Automated COVID-19 diagnosis
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This repo contains the code created by Elien Martens during IAESTE internship summer 2021, Technical University of Kosice (Slovakia).
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## Data
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The [Interspeech Computational Paralinguistics ChallengE (ComParE) 2021](vhttp://www.compare.openaudio.eu/now/) proposes two challenges related to COVID-19 detection based on audio samples. Such samples represent speech and cough audio from both healthy and infected speakers. The COVID-19 Speech Sub-Challenge (CSS) offers 3.24 hours of audio recordings containing speech samples, while the COVID19 Cough Sub-Challenge (CCS) provides 1.63 hours of cough samples.
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The COVID-19 datasets can be obtained through The University of Cambridge.
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## How it works
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- clone repository
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- add cough or speech dataset (dist folder) (see [Data](##data) section), so that the structure is the following:
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```
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CovidSpeechChallenge
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|-- dist/
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|-- lab/
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|-- wav/
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|-- features/
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|-- results/
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|-- src/
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|-- vggish/
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|-- run_experiments.sh
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```
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- run ```run_experiments.sh``` to do the feature extraction, SVM training and prediction for each features combination
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## About the code
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- The ```features/``` folder will contain the extracted features after running the feature extraction codes. These are not included in this repository to limit the storage.
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- The ```results/``` contains a subfolder for each experiment with the final predictions for devel and test subset (saved as csv file) + plot of the normalized confusion matrix saved as jpg image (only for predictions test subset).
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This folder of the repository contains the results for the speech audio data.
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- The ```src/``` folder contains the python files for all feature extraction and SVMs
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- The ```vggish/``` folder contains the code necessary for VGGish and is downloaded from [https://modelzoo.co/model/audioset](https://modelzoo.co/model/audioset).
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- Finally ```run_experiments.sh``` is a bash script that can be modified to only run parts of the experiments. |